DC FieldValueLanguage
dc.contributor.authorNtalianis, Klimis-
dc.contributor.authorMorano, Pierluigi-
dc.contributor.authorTajani, Francesco-
dc.date.accessioned2024-07-19T07:54:11Z-
dc.date.available2024-07-19T07:54:11Z-
dc.date.issued2018-09-18-
dc.identifierscopus-85049499092-
dc.identifier.issn1463-578X-
dc.identifier.other85049499092-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2749-
dc.description.abstractPurpose: As regards the assessment of the market values of properties that compose real estate portfolios, the purpose of this paper is to propose and test an automated valuation model. In particular, the method defined allows for providing for objective, reliable and “quick” valuations of the assets in the phases of periodic reviews of the property values. Design/methodology/approach: Aiming at both predictive and interpretative purposes, the method, based on multi-objective genetic algorithms to search those model expressions that simultaneously maximize the accuracy of the data and the parsimony of the mathematical functions, is applied to a sample data of office properties characterized by medium and large size, located in the city of Milan (Italy) and sold in the period between 2004 and 2015. Findings: The model obtained could be an integration of the canonical methodologies (market approach, income approach, cost approach) implemented in the assessment of the market values of properties, so as to provide an additional tool to verify the results. In particular, the inclusion of economic variables in the model is consistent with the need to reiterate the valuations, contextualizing them to the locational characteristics and to the current property cycle phase in the specific area. Practical implications: The model can be applied by all the operators involved in the periodic reviews of the values of property portfolios: from real estate funds’ insiders, in order to monitor the values obtained through the canonical approaches, to the public institutions, such as the revenue agencies, in order to ensure the fair payment of the taxes through the updating values of the properties according to the actual and current market trends. Originality/value: The method proposed can be a valid support for all public and private entities that hold significant property assets and that, for various reasons (periodic reviews of the balance sheets, sales, enhancement, investment, etc.), require cyclical updated values of the properties. The automated valuation model developed can be used for the assessment of “comparison” values with the estimates values obtained by other assessment techniques, in order to ensure a further monitoring tool of the results from the subjects involved.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Property Investment and Financeen_US
dc.subjectAutomated valuation modelen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMarket renten_US
dc.subjectMarket valueen_US
dc.subjectMass appraisalen_US
dc.subjectReal estateen_US
dc.titleAutomated valuation models for real estate portfolios: a method for the value updates of the property assetsen_US
dc.typeArticleen_US
dc.identifier.doi10.1108/JPIF-10-2017-0067en_US
dc.identifier.scopus2-s2.0-85049499092-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume36en_US
dc.relation.issue4en_US
dc.identifier.spage324en_US
dc.identifier.epage347en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.openairetypeArticle-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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